Skip to main content

Terms and Conditions

 Terms and Conditions of Salim Wireless


Below are the Terms and Conditions for use of https://www.salimwireless.com.


Please read these carefully. If you need to contact us regarding any aspect of the following terms of use of our website, please contact us at iamsalim002@gmail.com


By accessing the content of Salim Wireless ( hereafter referred to as a website ) you agree to the terms and conditions set out herein and also accept our privacy policy. If you do not agree to any of the terms and conditions you should not continue to use the website and leave immediately.


You agree that you shall not use the website for any illegal purposes and that you will respect all applicable laws and regulations.


You agree not to use Salim Wireless! website in a way that may impair the performance, corrupt or manipulate the content or information available on the website or reduce the overall functionality of the website.


You agree not to compromise the security of the website or attempt to gain access to secured areas of the website or attempt to access any sensitive information you may believe exist on the website or server where it is hosted.


You agree to be fully responsible for any claim, expense, losses, liability, costs including legal fees incurred by us arising from any infringement of the terms and conditions in this agreement and to which you will have agreed if you continue to use the website.


The reproduction, distribution in any method whether online or offline is strictly not prohibited. The work on the website and the images, logos, text and other such information is not the property of https://www.salimwireless.com ( unless otherwise stated ).


Disclaimer


Though we strive to be completely accurate in the information that is presented on our site and attempt to keep it as up to date as possible, in some cases, some of the information you find on the website may be slightly outdated.


Salim Wireless reserves the right to make any modifications or corrections to the information you find on the website at any time without notice.


Change to the Terms and Conditions of Use


We reserve the right to make changes and to revise the above-mentioned Terms and Conditions of use.


Last Revised: 21-05-2022

People are good at skipping over material they already know!

View Related Topics to







Contact Us

Name

Email *

Message *

Popular Posts

Online Simulator for ASK, FSK, and PSK

Try our new Digital Signal Processing Simulator!   Start Simulator for binary ASK Modulation Message Bits (e.g. 1,0,1,0) Carrier Frequency (Hz) Sampling Frequency (Hz) Run Simulation Simulator for binary FSK Modulation Input Bits (e.g. 1,0,1,0) Freq for '1' (Hz) Freq for '0' (Hz) Sampling Rate (Hz) Visualize FSK Signal Simulator for BPSK Modulation ...

Constellation Diagrams of ASK, PSK, and FSK

📘 Overview of Energy per Bit (Eb / N0) 🧮 Online Simulator for constellation diagrams of ASK, FSK, and PSK 🧮 Theory behind Constellation Diagrams of ASK, FSK, and PSK 🧮 MATLAB Codes for Constellation Diagrams of ASK, FSK, and PSK 📚 Further Reading 📂 Other Topics on Constellation Diagrams of ASK, PSK, and FSK ... 🧮 Simulator for constellation diagrams of m-ary PSK 🧮 Simulator for constellation diagrams of m-ary QAM BASK (Binary ASK) Modulation: Transmits one of two signals: 0 or -√Eb, where Eb​ is the energy per bit. These signals represent binary 0 and 1.    BFSK (Binary FSK) Modulation: Transmits one of two signals: +√Eb​ ( On the y-axis, the phase shift of 90 degrees with respect to the x-axis, which is also termed phase offset ) or √Eb (on x-axis), where Eb​ is the energy per bit. These signals represent binary 0 and 1.  BPSK (Binary PSK) Modulation: Transmits one of two signals...

BER vs SNR for M-ary QAM, M-ary PSK, QPSK, BPSK, ...

📘 Overview of BER and SNR 🧮 Online Simulator for BER calculation of m-ary QAM and m-ary PSK 🧮 MATLAB Code for BER calculation of M-ary QAM, M-ary PSK, QPSK, BPSK, ... 📚 Further Reading 📂 View Other Topics on M-ary QAM, M-ary PSK, QPSK ... 🧮 Online Simulator for Constellation Diagram of m-ary QAM 🧮 Online Simulator for Constellation Diagram of m-ary PSK 🧮 MATLAB Code for BER calculation of ASK, FSK, and PSK 🧮 MATLAB Code for BER calculation of Alamouti Scheme 🧮 Different approaches to calculate BER vs SNR What is Bit Error Rate (BER)? The abbreviation BER stands for Bit Error Rate, which indicates how many corrupted bits are received (after the demodulation process) compared to the total number of bits sent in a communication process. BER = (number of bits received in error) / (total number of tran...

Q-function in BER vs SNR Calculation

Q-function in BER vs. SNR Calculation In the context of Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) calculations, the Q-function plays a significant role, especially in digital communications and signal processing . What is the Q-function? The Q-function is a mathematical function that represents the tail probability of the standard normal distribution. Specifically, it is defined as: Q(x) = (1 / sqrt(2Ï€)) ∫â‚“∞ e^(-t² / 2) dt In simpler terms, the Q-function gives the probability that a standard normal random variable exceeds a value x . This is closely related to the complementary cumulative distribution function of the normal distribution. The Role of the Q-function in BER vs. SNR The Q-function is widely used in the calculation of the Bit Error Rate (BER) in communication systems, particularly in systems like Binary Phase Shift Ke...

Theoretical BER vs SNR for m-ary PSK and QAM

Relationship Between Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) The relationship between Bit Error Rate (BER) and Signal-to-Noise Ratio (SNR) is a fundamental concept in digital communication systems. Here’s a detailed explanation: BER (Bit Error Rate): The ratio of the number of bits incorrectly received to the total number of bits transmitted. It measures the quality of the communication link. SNR (Signal-to-Noise Ratio): The ratio of the signal power to the noise power, indicating how much the signal is corrupted by noise. Relationship The BER typically decreases as the SNR increases. This relationship helps evaluate the performance of various modulation schemes. BPSK (Binary Phase Shift Keying) Simple and robust. BER in AWGN channel: BER = 0.5 × erfc(√SNR) Performs well at low SNR. QPSK (Quadrature...

Wiener Filter Theory: Equations, Error Signal, and MSE

  Assuming known stationary signal and noise spectra and additive noise, the Wiener filter is a filter used in signal processing to provide an estimate of a desired or target random process through linear time-invariant (LTI) filtering of an observed noisy process. The mean square error between the intended process and the estimated random process is reduced by the Wiener filter. Fig: Block diagram view of the FIR Wiener filter for discrete series. An input signal x[n] is convolved with the Wiener filter g[n] and the result is compared to a reference signal s[n] to obtain the filtering error e[n]. In the big picture, the signal is attenuated and added with noise, then the signal is passed through a Wiener filter. And the function of the Wiener filter is to minimize the mean square error between the filter output of the received signal and the reference signal by adjusting the Wiener filter tap coefficient.   Description...

MATLAB code for Pulse Code Modulation (PCM) and Demodulation

📘 Overview & Theory 🧮 Quantization in Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Code Modulation (PCM) 🧮 MATLAB Code for Pulse Amplitude Modulation and Demodulation of Digital data 🧮 Other Pulse Modulation Techniques (e.g., PWM, PPM, DM, and PCM) 📚 Further Reading MATLAB Code for Pulse Code Modulation clc; close all; clear all; fm=input('Enter the message frequency (in Hz): '); fs=input('Enter the sampling frequency (in Hz): '); L=input('Enter the number of the quantization levels: '); n = log2(L); t=0:1/fs:1; % fs nuber of samples have tobe selected s=8*sin(2*pi*fm*t); subplot(3,1,1); t=0:1/(length(s)-1):1; plot(t,s); title('Analog Signal'); ylabel('Amplitude--->'); xlabel('Time--->'); subplot(3,1,2); stem(t,s);grid on; title('Sampled Sinal'); ylabel('Amplitude--->'); xlabel('Time--->'); % Quantization Process vmax=8; vmin=-vmax; %to quanti...

Wide Sense Stationary Signal (WSS)

Q & A and Summary Stationary and Wide Sense Stationary Process A stochastic process {…, X t-1 , X t , X t+1 , X t+2 , …} consisting of random variables indexed by time index t is a time series. The stochastic behavior of {X t } is determined by specifying the probability density or mass functions (pdf’s): p(x t1 , x t2 , x t3 , …, x tm ) for all finite collections of time indexes {(t 1 , t 2 , …, t m ), m < ∞} i.e., all finite-dimensional distributions of {X t }. A time series {X t } is strictly stationary if p(t 1 + Ï„, t 2 + Ï„, …, t m + Ï„) = p(t 1 , t 2 , …, t m ) , ∀Ï„, ∀m, ∀(t 1 , t 2 , …, t m ) . Where p(t 1 + Ï„, t 2 + Ï„, …, t m + Ï„) represents the cumulative distribution function of the unconditional (i.e., with no reference to any particular starting value) joint distribution. A process {X t } is said to be strictly stationary or strict-sense stationary if Ï„ doesn’t affect the function p. Thus, p is not a function of time. A time series {X t } ...